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Distributed Process Management

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Presentation on theme: "Distributed Process Management"— Presentation transcript:

1 Distributed Process Management
Chapter 15

2 Process Migration Transfer of sufficient amount of the state of a process from one computer to another The process executes on the target machine

3 Motivation Load sharing Communications performance
Move processes from heavily loaded to lightly load systems Communications performance Processes that interact intensively can be moved to the same node to reduce communications cost May be better to move process to where the data reside when the data is large

4 Motivation Availability Utilizing special capabilities
Long-running process may need to move because the machine it is running on will be down Utilizing special capabilities Process can take advantage of unique hardware or software capabilities

5 Initiation of Migration
Operating system When goal is load balancing Process When goal is to reach a particular resource

6 What is Migrated? Must destroy the process on the source system and create it on the target system Process image and process control block and any links must be moved

7 Example of Process Migration

8 Example of Process Migration

9 What is Migrated? Eager (all):Transfer entire address space
No trace of process is left behind If address space is large and if the process does not need most of it, then this approach my be unnecessarily expensive

10 What is Migrated? Precopy: Process continues to execute on the source node while the address space is copied Pages modified on the source during precopy operation have to be copied a second time Reduces the time that a process is frozen and cannot execute during migration

11 What is Migrated? Eager (dirty): Transfer only that portion of the address space that is in main memory and have been modified Any additional blocks of the virtual address space are transferred on demand The source machine is involved throughout the life of the process

12 What is Migrated? Copy-on-reference: Pages are only brought over when referenced Has lowest initial cost of process migration Flushing: Pages are cleared from main memory by flushing dirty pages to disk Relieves the source of holding any pages of the migrated process in main memory

13 Negotiation of Migration
Migration policy is responsibility of Starter utility Starter utility is also responsible for long- term scheduling and memory allocation Decision to migrate must be reached jointly by two Starter processes (one on the source and one on the destination)


15 Eviction Destination system may refuse to accept the migration of a process to itself If a workstation is idle, process may have been migrated to it Once the workstation is active, it may be necessary to evict the migrated processes to provide adequate response time

16 Distributed Global States
Operating system cannot know the current state of all process in the distributed system A process can only know the current state of all processes on the local system Remote processes only know state information that is received by messages These messages represent the state in the past

17 Example Bank account is distributed over two branches
The total amount in the account is the sum at each branch At 3 PM the account balance is determined Messages are sent to request the information

18 Example

19 Example If at the time of balance determination, the balance from branch A is in transit to branch B The result is a false reading

20 Example

21 Example All messages in transit must be examined at time of observation Total consists of balance at both branches and amount in message

22 Example If clocks at the two branches are not perfectly synchronized
Transfer amount at 3:01 from branch A Amount arrives at branch B at 2:59 At 3:00 the amount is counted twice

23 Example

24 Some Terms Channel State
Exists between two processes if they exchange messages State Sequence of messages that have been sent and received along channels incident with the process

25 Some Terms Snapshot Global state Distributed Snapshot
Records the state of a process Global state The combined state of all processes Distributed Snapshot A collection of snapshots, one for each process

26 Inconsistent Global State

27 Consistent Global State

28 Distributed Snapshot Algorithm

29 Distributed Snapshot Algorithm
Process 1 Outgoing channels 2 sent 1, 2, 3, 4, 5, 6 3 sent 1, 2, 3, 4, 5, 6 Incoming channels Process 3 2 sent 1, 2, 3, 4, 5, 6, 7, 8 1 received 1, 2, 3 stored 4, 5, 6 2 received 1, 2, 3 stored 4 4 received 1, 2, 3 Process 2 3 sent 1, 2, 3, 4 4 sent 1, 2, 3, 4 1 received 1, 2, 3, 4 stored 5, 6 3 received 1, 2, 3, 4, 5, 6, 7, 8 Process 4 3 sent 1, 2, 3 2 received 1, 2 stored 3, 4

30 Distributed Mutual Exclusion Concepts
Mutual exclusion must be enforced: only one process at a time is allowed in its critical section A process that halts in its noncritical section must do so without interfering with other processes It must not be possible for a process requiring access to a critical section to be delayed indefinitely: no deadlock or starvation

31 Distributed Mutual Exclusion Concepts
When no process is in a critical section, any process that requests entry to its critical section must be permitted to enter without delay No assumptions are made about relative process speeds or number of processors A process remains inside its critical section for a finite time only


33 Centralized Algorithm for Mutual Exclusion
One node is designated as the control node This node control access to all shared objects Only the control node makes resource- allocation decision All necessary information is concentrated in the control node If control node fails, mutual exclusion breaks down

34 Distributed Algorithm
All nodes have equal amount of information, on average Each node has only a partial picture of the total system and must make decisions based on this information All nodes bear equal responsibility for the final decision

35 Distributed Algorithm
All nodes expend equal effort, on average, in effecting a final decision Failure of a node, in general, does not result in a total system collapse There exits no systemwide common clock with which to regulate the time of events

36 Ordering of Events Events must be order to ensure mutual exclusion and avoid deadlock Clocks are not synchronized Communication delays

37 Ordering of Events Need to consistently say that one event occurs before another event Messages are sent when want to enter critical section and when leaving critical section Time-stamping Orders events on a distributed system System clock is not used

38 Time-Stamping Each system on the network maintains a counter which functions as a clock Each site has a numerical identifier When a message is received, the receiving system sets is counter to one more than the maximum of its current value and the incoming time-stamp (counter)

39 Time-Stamping If two messages have the same time- stamp, they are ordered by the number of their sites For this method to work, each message is sent from one process to all other processes Ensures all sites have same ordering of messages For mutual exclusion and deadlock all processes must be aware of the situation




43 Token-Passing Approach
Pass a token among the participating processes The token is an entity that at any time is held by one process The process holding the token may enter its critical section without asking permission When a process leaves its critical section, it passes the token to another process

44 Deadlock in Resource Allocation
Mutual exclusion Hold and wait No preemption Circular wait

45 Phantom Deadlock

46 Deadlock Prevention Circular-wait condition can be prevented by defining a linear ordering of resource types Hold-and-wait condition can be prevented by requiring that a process request all of its required resource at one time, and blocking the process until all requests can be granted simultaneously

47 Deadlock Avoidance Distributed deadlock avoidance is impractical
Every node must keep track of the global state of the system The process of checking for a safe global state must be mutually exclusive Checking for safe states involves considerable processing overhead for a distributed system with a large number of processes and resources

48 Distributed Deadlock Detection
Each site only knows about its own resources Deadlock may involve distributed resources Centralized control – one site is responsible for deadlock detection Hierarchical control – lowest node above the nodes involved in deadlock Distributed control – all processes cooperate in the deadlock detection function

49 Deadlock in Message Communication
Mutual Waiting Deadlock occurs in message communication when each of a group of processes is waiting for a message from another member of the group and there are no messages in transit


51 Deadlock in Message Communication
Unavailability of Message Buffers Well known in packet-switching data networks Example: buffer space for A is filled with packets destined for B. The reverse is true at B.

52 Direct Store-and-Forward Deadlock

53 Deadlock in Message Communication
Unavailability of Message Buffers For each node, the queue to the adjacent node in one direction is full with packets destined for the next node beyond


55 Structured Buffer Pool

56 Finite Channels Lead to Deadlock

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